On penalized likelihood estimation for a non-proportional hazards regression model
Copyright policy ) Devarajan, Karthik; Ebrahimi, Nader;
On penalized likelihood estimation for a non-proportional hazards regression model
In this paper, a semi-parametric generalization of the Cox model that permits crossing hazard curves is described. A theoretical framework for estimation in this model is developed based on penalized likelihood methods. It is shown that the optimal solution to the baseline hazard, baseline cumulative hazard and their ratio are hyperbolic splines with knots at the distinct failure times.
- Northwestern University United States
- Northern Illinois University United States
- Fox Chase Cancer Center United States
Censored data models, Estimation in survival analysis and censored data, crossing hazards, splines, proportional hazards, penalized likelihood, censored survival data analysis
Censored data models, Estimation in survival analysis and censored data, crossing hazards, splines, proportional hazards, penalized likelihood, censored survival data analysis
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selected citations
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These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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